Nanoparticle self-assemblies with modern complexity

Journal Article · 10 April 2024 · MRS Bulletin

DOI: https://doi.org/10.1557/s43577-024-00700-1 · OSTI ID:2478151

Chen, Qian  ^[1]; Zhang, Xin ^[2]

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1. Univ. of Illinois at Urbana-Champaign, IL (United States)
2. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Energy Frontier Research Centers (EFRC) (United States). Interfacial Dynamics in Radioactive Environments and Materials (IDREAM)
• Sponsoring Organization: USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 2478151
• Report Number(s): PNNL-SA--196846
• Journal Information: MRS Bulletin, Journal Name: MRS Bulletin Journal Issue: 4 Vol. 49; ISSN 0883-7694
• Publisher: Materials Research SocietyCopyright Statement
• Country of Publication: United States
• Language: English